Transcribed
Fraud Detection through Data Analysis
oO DATA ANALYSIS Techniques FOR FRAUD DETECTION COST OF FRAUD AT HE NDO 37 I SE eeraeyar period 726 FRAUD CASESma FBI INURANCEAuE CS THE 540 LION ANNY IM s P HEALTH CARE FRAUD ro cosr ovE SSO BUON COST A SIL MLN PER VEAR 36% 43% data theft ATI praductivity 3 BASIC STEPS TO DATA ANALYSIS BENTRICATON ANATN ANALNON DATA ANALYSIS TECHNIQUES VISUALIZATION OUTLIER DETECTION EXAMPLE CONTINUOUS MONITORING & ANOMALY DETECTION EXAMPLE REGRESSION ANALYSIS EXAMPLE SEMANTIC MODELING EXAMPLE NEURAL NETWORK EXAMPLE
Fraud Detection through Data Analysis
shared by andrewdeen on Sep 27
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In recent years, the number of people and businesses falling victim to fraud has increased at an alarming rate. As technology continues to improve, fraudsters are finding new and creative methods to c...
ontinue their work.
Fraudulent practices targeting businesses are growing at an alarming rate and are costing industries billions of dollars. In the insurance industry alone, $40 billion per year is lost as a result of fraud. The theft of money is not the only culprit; 36 percent of total loss due to fraud is directly related to business disruption and loss of productivity.
Health care fraud estimated to cost over $500 billion.
Cybercrime in 2013 cost an average $11.56 million per year.
Fraud prevention requires innovative solutions that can both fight fraudulent practices and protect individuals and businesses from disruption and loss of productivity.
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